Applied AI Engineering: Build Real-World AI Applications

Modern software engineering is rapidly evolving, requiring developers to build applications that leverage artificial intelligence. If you want to transition from traditional programming to engineering intelligent systems, you need a practical, code-first approach. This text-based course guides you from the foundational concepts of artificial intelligence to constructing functional, AI-driven applications. You will learn how to connect software to powerful AI models, handle data effectively, and implement modern architectural patterns. What you'll learn: - Understand the core concepts of generative AI, large language models, and the modern AI engineering stack. - Apply prompt engineering techniques to programmatically control model behavior and outputs. - Integrate external APIs and model endpoints directly into your application code. - Configure vector databases and implement retrieval-augmented generation (RAG) to ground AI responses in custom data. - Design error-handling, caching, and evaluation workflows to ensure reliable application performance. You will start by exploring key terminology and foundational architectures before progressing to hands-on implementation. Each module provides clear explanations and code snippets that demonstrate how to connect, query, and secure your AI integrations. This course is designed for software developers and tech professionals who want to build with AI without needing a deep background in advanced mathematics or machine learning theory. Start reading today to begin building the next generation of intelligent software.